FacebookAI/roberta-large

fill-mask model by FacebookAI

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Pretrained model on English language using a masked language modeling (MLM) objective. It was introduced in this paper and first released in this repository. This model is case-sensitive: it makes a difference between english and English. Disclaimer: The team releasing RoBERTa did not write a model card for this model so this model card has been written by the Hugging Face team. RoBERTa is a transformers model pretrained on a large corpus of English data in a self-supervised fashion. This means it was pretrained on the raw texts only, with no humans labelling them in any way (which is why it can use lots of publicly available data) with an automatic process to generate inputs and labels from those texts. More precisely, it was pretrained with the Masked language modeling (MLM) objective. Taking a sentence, the model randomly masks 15% of the words in the input then run the entire…

FacebookAI/roberta-large on Hugging Face A short preview, not the full document.

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Inside the original model card — Document outline
  1. RoBERTa large model
  2. Model description
  3. Intended uses & limitations
  4. How to use
  5. Limitations and bias
  6. Training data
  7. Training procedure
  8. Preprocessing
  9. Pretraining
  10. Evaluation results
  11. BibTeX entry and citation info

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Documentation belongs to its respective authors. Reported project/model license: mit. A listing is not a grant of reuse or training rights. Confirm the document’s own terms at the source.

Model overview

FacebookAI/roberta-large is a fill-mask model repository published by FacebookAI on Hugging Face. The source reports the transformers library.

This page summarizes Hub metadata. For intended use, training data, evaluation results and limitations, consult the original model card.

Model facts

Task
fill-mask
Library
transformers
Recent downloads (30 days)
7,079,439
Cumulative likes
346
Hugging Face trending score
0
Reported safetensors parameters
355,412,571
Architecture
RobertaForMaskedLM
License
mit
Access
Not gated by Hugging Face
Created
2022-03-02T23:29:04.000Z
Last modified
2024-02-19T12:47:04.000Z

Compatibility and lineage

Reported languages: en

Base-model lineage was not included.

Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.

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Model card and usage instructions

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Source and freshness

Source: Hugging Face Hub. Metadata observed 2026-11-01T06:49:31.990Z. Daily imports are snapshots, not real-time monitoring.

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